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dc.contributor.author
Abdelhadi, Dina
dc.contributor.author
Renes, Joseph M.
dc.date.accessioned
2021-01-11T08:49:28Z
dc.date.available
2020-09-15T03:48:13Z
dc.date.available
2020-09-17T09:03:22Z
dc.date.available
2021-01-11T08:49:28Z
dc.date.issued
2020
dc.identifier.isbn
978-1-7281-6432-8
en_US
dc.identifier.isbn
978-1-7281-6431-1
en_US
dc.identifier.isbn
978-1-7281-6433-5
en_US
dc.identifier.other
10.1109/ISIT44484.2020.9173948
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/440502
dc.description.abstract
Anshu et al. recently introduced "partially" smoothed information measures and used them to derive tighter bounds for several information-processing tasks, including quantum state merging and privacy amplification against quantum adversaries [arXiv:1807.05630 [quant-ph]]. Yet, a tight second- order asymptotic expansion of the partially smoothed conditional min-entropy in the i.i.d. setting remains an open question. Here we establish the second-order term in the expansion for pure states, and find that it differs from that of the original "globally" smoothed conditional min-entropy. Remarkably, this reveals that the second-order term is not uniform across states, since for other classes of states the second-order term for partially and globally smoothed quantities coincides. By relating the task of quantum compression to that of quantum state merging, our derived expansion allows us to determine the second-order asymptotic expansion of the optimal rate of quantum data compression. This closes a gap in the bounds determined by Datta and Leditzky [IEEE Trans. Inf. Theory 61, 582 (2015)], and shows that the straightforward compression protocol of cutting off the eigenspace of least weight is indeed asymptotically optimal at second order. © 2020 IEEE.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
Second-order asymptotics of quantum data compression from partially-smoothed conditional entropy
en_US
dc.type
Conference Paper
dc.date.published
2020-08-24
ethz.book.title
2020 IEEE International Symposium on Information Theory (ISIT)
en_US
ethz.pages.start
1846
en_US
ethz.pages.end
1851
en_US
ethz.event
IEEE International Symposium on Information Theory (ISIT 2020) (virtual)
en_US
ethz.event.location
Los Angeles, CA, USA
en_US
ethz.event.date
June 21-26, 2020
en_US
ethz.notes
Due to the Corona virus (COVID-19) the conference was conducted virtually.
en_US
ethz.identifier.scopus
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02010 - Dep. Physik / Dep. of Physics::02511 - Institut für Theoretische Physik / Institute for Theoretical Physics::03781 - Renner, Renato / Renner, Renato
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02010 - Dep. Physik / Dep. of Physics::02511 - Institut für Theoretische Physik / Institute for Theoretical Physics::03781 - Renner, Renato / Renner, Renato
ethz.date.deposited
2020-09-15T03:48:37Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2020-09-17T09:03:35Z
ethz.rosetta.lastUpdated
2022-03-29T04:46:03Z
ethz.rosetta.versionExported
true
ethz.COinS
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